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Updated: Jun 9, 2025

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Published on: October 25, 2018

Salmonella enterica virulence databases and bioinformatic analysis tools development.

Jing Han^1,2, Hailin Tang³, Shaohua Zhao⁴

¹Division of Microbiology, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, 72079, USA. jing.han1@fda.hhs.gov.

Scientific Reports

|October 25, 2024

Summary

This summary is machine-generated.

A new Salmonella Virulence Database and analysis tools aid in assessing pathogen virulence. These resources enhance understanding of Salmonella virulence factors and profiles for improved food safety and disease control strategies.

Keywords:

Salmonella Database Virulence genes WGS analyses tools

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Last Updated: Jun 9, 2025

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Published on: October 25, 2018

Automated Analysis of Intracellular Phenotypes of Salmonella Using ImageJ

Automated Analysis of Intracellular Phenotypes of Salmonella Using ImageJ

Published on: August 9, 2022

A High-throughput Platform for the Screening of Salmonella spp./Shigella spp.

A High-throughput Platform for the Screening of Salmonella spp./Shigella spp.

Published on: November 7, 2018

Area of Science:

Microbiology
Bioinformatics
Genomics

Background:

Salmonella enterica is a major foodborne pathogen causing significant global illness.
Genetic diversity in Salmonella influences infectivity, disease severity, and antimicrobial resistance.
Existing bioinformatics tools for Salmonella virulence assessment have limitations.

Purpose of the Study:

To construct a comprehensive Salmonella Virulence Database.
To develop novel bioinformatics tools for virulence factor analysis.
To facilitate improved assessment of Salmonella virulence profiles.

Main Methods:

Developed a non-redundant database of putative Salmonella virulence factors.
Created two bioinformatic tools: Virulence Factor Profile Assessment and Comparison.
Validated the database and tools using whole genome sequencing (WGS) data from 43,853 Salmonella isolates across 14 serovars.

Main Results:

The Salmonella Virulence Database and associated tools effectively facilitated virulence assessment.
Enhanced understanding of virulence profiles among different Salmonella isolates and serovars.
Demonstrated the utility of WGS data for comprehensive virulence analysis.

Conclusions:

The developed database and tools provide a valuable resource for researchers studying Salmonella virulence.
Public availability of these resources will aid in pathogen control and risk assessment for human illnesses.
This work advances the comprehensive assessment of Salmonella virulence, informing public health strategies.